{"id":"W1604810899","doi":"","title":"Commentary on \"Model fit and model selection\"","year":2007,"lang":"en","type":"article","venue":"Canadian parliamentary review","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Econometrics; Model selection; Econometric model; Computer science; Selection (genetic algorithm); Variance (accounting); Range (aeronautics); Bayesian probability; Bayesian inference; Economics; Dynamic stochastic general equilibrium; Macroeconomics; Monetary policy; Machine learning; Artificial intelligence; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0804895,0.002140044,0.005881598,0.006285963,0.009526957,0.01137195,0.01566517,0.04816112,0.007689051],"category_scores_gemma":[0.3435905,0.002159541,0.004257341,0.008505442,0.01779852,0.006800648,0.004948136,0.05795921,0.004462788],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0266561,"about_ca_system_score_gemma":0.06282519,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4704454,"about_ca_topic_score_gemma":0.4736743,"domain_scores_codex":[0.9046513,0.03897632,0.007701625,0.007225361,0.03702592,0.004419497],"domain_scores_gemma":[0.6192184,0.2715172,0.009517935,0.008910309,0.08499886,0.005837324],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003045425,0.000007136562,0.0001042308,0.0001994065,0.00005488236,0.00005040743,0.0001925434,0.0002356031,0.00001819915,0.01540732,0.9793418,0.004358048],"study_design_scores_gemma":[0.0002771844,0.0000270908,0.001829225,0.003855607,0.0003311278,0.000187685,0.0005855316,0.001728619,0.0002279448,0.06160477,0.9291444,0.0002007681],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0001139405,0.007513214,0.000921468,0.9541444,0.0347568,0.00001481905,0.0004582815,0.00005171661,0.00202532],"genre_scores_gemma":[0.005502192,0.00451078,0.001460464,0.9441108,0.04126011,0.00009210168,0.0001954029,0.0001443787,0.002723835],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.4704454,"threshold_uncertainty_score":0.9354142,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09819150713343558,"score_gpt":0.2604961366210152,"score_spread":0.1623046294875796,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}